In a scene having video monitor such as a station and a ticket office and so on, estimation of queuing time is performed mainly depending on the number of pedestrians in a current queue and a motion speed of each queue. However, it is very hard for a user to know in advance the motion speed of each queue during a previous time interval, so that a selection is always made only based on a queue length of each queue. In this way, it is always assumed that a processing speed of each queue is the same. However, in fact, processing efficiency of each queue may be quiet different due to different staff members. It is very hard to estimate an approximate waiting time only based on the queue length. If a waiting time of each current queue can be estimated according to video data automatically, then the waiting time of the user can be saved greatly and work efficiency can be raised.
Therefore, it is desired to provide a video monitoring method and a video monitoring system based on a depth video, which are capable of automatically intercepting the queue length in a physical space as well as the motion speed of the queue in a three-dimensional space based on the depth video, to estimate the queuing time of each queue successively. Then, a suggestion on a queue that a current user queues up is given to the user.